Yuki Kadokawa

Current Position

Institute: Nara Institute of Science and Technology

Position: Project Assistant Professor

Education

• Doctor of Engineering, Nara Institute of Science and Technology, Program of Information Science and Engineering, Japan, 2024
• Master of Engineering, Nara Institute of Science and Technology, Program of Information Science and Engineering, Japan, 2021
• Bachelor of Engineering, Toyama Prefectural University, Department of Intelligent Robotics, Japan, 2019

Publicatin

International Journal

1. Yuki Kadokawa, Hirotaka Tahara, and Takamitsu Matsubara, "Progressive-Resolution Policy Distillation: Leveraging Coarse-Resolution Simulations for Time-Efficient Fine-Resolution Policy Learning", IEEE Robotics and Automation Letters (RA-L), under review
2. Yuki Kadokawa, Tomohito Kodera, Yoshihisa Tsurumine, Shinya Nishimura, and Takamitsu Matsubara, "Robust Iterative Value Conversion: Deep Reinforcement Learning for Neurochip-driven Edge Robots", Robotics and Autonomous Systems (RAS), 2024 [Paper] [Video]
3. Yuki Kadokawa, Lingwei Zhu, Yoshihisa Tsurumine and Takamitsu Matsubara, "Cyclic Policy Distillation: Sample-Efficient Sim-to-Real Reinforcement Learning with Domain Randomization", Robotics and Autonomous Systems (RAS), 2023 [Paper] [Video]
4. Yuki Kadokawa, Yoshihisa Tsurumine, and Takamitsu Matsubara, "Binarized P-Network: Deep Reinforcement Learning of Robot Control from Raw Images on FPGA", IEEE Robotics and Automation Letters (RA-L), vol. 6, no. 4, pp. 8545-8552, 2021 (Student Paper Award) [Paper] [Video]

International Conference

1. Yuki Kadokawa, Masashi Hamaya, and Kazutoshi Tanaka, "Learning Robotic Powder Weighing from Simulation for Laboratory Automation", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023 [Project Page] [Paper] [Video]
2. Yuki Kadokawa, Yoshihisa Tsurumine, and Takamitsu Matsubara, "Binarized P-Network: Deep Reinforcement Learning of Robot Control from Raw Images on FPGA", IEEE International Conference on Robotics and Automation (ICRA, RA-L option), 2023 [Paper] [Video]

Award

1. Nara Institute of Science and Technology, Symposium of University Fellowship, Outstanding Student Award, 2022 [Award Page]
2. IEEE Kansai Section, Student Paper Award, 2022 Student Award, 2022 [NAIST Award Page] [IEEE Award Page]
3. Toyama Prefectural University, Best Student of the Year, 2019
4. Toyama Mechanical and Electrical Industries Association, Monozukuri in Toyama, Grand Prize, 2018
5. Japan Society for Design Engineering, Design Competition, Best Presentation Award, 2018
6. Japan Society for Design Engineering, Design Competition, 3rd Place (National Finals 3/10), 2018
7. Japan Society for Design Engineering, Research Presentation, Best Student Presentation Award, 2018
8. Japan Society for Design Engineering, Design Competition, Best Presentation Award, 2017
9. Toyama Prefectural Takaoka Kogei High School, Best Student of the Year, 2015

Scholarship & Grant

1. Japan Student Services Organization, Scholarship (Return Exemption Full Amount), 2023
2. Japan Society for the Promotion of Science, Research Fellowship for Young Scientists: DC2 (Obtaining Research Funding and Salaries), 2023
3. Japan Science and Technology Agency, Research Fellowship (Obtaining Research Funding and Salaries), 2022 [Interview Page]
4. Japan Student Services Organization, Scholarship (Return Exemption Half Amount), 2021
5. Nara Institute of Science and Technology, Outstanding Student Scholarship (Tuition Exemption), 2021

Work history

1. August 2023 - October 2023, Robotics Systems Lab (ETH Zurich), Visiting Researcher
2. April 2022 - March 2023, OMRON SINIC X Corporation, Research Internship [Project Page] [Paper] [Video]
3. December 2018 - March 2019, Aluminum Factory Corporation, Part-time Job for Making 3D-CAD Models

Research Field

• Reinforcement Learning, Deep Learning, Robotics
• Sim-to-Real, Domain Randomization
• Edge Robot, FPGA, Neurochip